Sum Rate Maximization and Performance Analysis of NOMA-Based IRS-Aided Uplink Visible Light Communication System

Achieving high data rates in uplink visible light communication (UVLC) systems while ensuring the safety of human eyes presents a significant challenge. This study investigates a UVLC system leveraging non-orthogonal multiple access (NOMA) and intelligent reflecting surfaces (IRS) to enhance the sum rate. The rate maximization problem is formulated based on the IRS attribute association matrix, and an optimization framework is developed to solve it. The proposed solution is validated through comprehensive simulations, demonstrating its effectiveness in improving system performance. Moreover, the impact of variation in transmit power and field of view on the sum rate with different numbers of IRS units is extensively studied. And the results demonstrate the effectiveness of the IRS over a system without the IRS.